This invention relates generally to methods and systems for conducting identity matching, and more particularly, to methods and systems for conducting efficient multi-modal biometric large scale 1:N identity matching.
Biometric fusion combines a plurality of biometric samples, of the same or different biometric modality, to yield higher accuracy and lower false accept rates during matching in large scale 1:N biometric matching systems. Known biometric fusion techniques include parallel fusion and cascade fusion. Parallel fusion techniques generally involve score-level fusion of individual biometric scores into a single composite score. However, known parallel fusion techniques always require biometric data for each modality to be matched.
Cascade fusion techniques generally execute a series of algorithms such that a subsequent algorithm is executed against candidate matches determined by a previous algorithm. However, cascade fusion assumes that every candidate always includes all the biometric modalities. When considering large populations, all members of the population rarely are able to provide all biometric modalities required by either parallel or cascade fusion techniques. For example, amputees may not be able to provide finger biometric data samples. Furthermore, when using data from legacy systems to conduct large scale 1:N identity matching, the legacy data may not include all the biometric data required by parallel and cascade fusion systems.
Known biometric matching systems fail to separate management of the overall population from the provisioning of the matching systems. Thus, using known biometric matching systems, it is difficult, time consuming and expensive to apply certain matching algorithms to data from specific groups of individuals within the overall population. Consequently, it appears that separating management of the overall population from the provisioning of the matching systems may facilitate easier application of certain matching algorithms against data from specific groups of individuals, and may thereby reduce associated time and costs.